A simple search for DoEvents brings up lots of results that lead, basically, to:
DoEvents is evil. Don't use it. Use threading instead.
The reasons generally cited are:
Re-entrancy issues
Poor performance
Usability issues (e.g. drag/drop over a disabled window)
But some notable Win32 functions such as TrackPopupMenu and DoDragDrop perform their own message processing to keep the UI responsive, just like DoEvents does.
And yet, none of these seem to come across these issues (performance, re-entrancy, etc.).
How do they do it? How do they avoid the problems cited with DoEvents? (Or do they?)
DoEvents() is dangerous. But I bet you do lots of dangerous things every day. Just yesterday I set off a few explosive devices (future readers: note the original post date relative to a certain American holiday). With care, we can sometimes account for the dangers. Of course, that means knowing and understanding what the dangers are:
Re-entry issues. There are actually two dangers here:
Part of the problem here has to do with the call stack. If you call .DoEvents() in a loop that itself handles messages that use DoEvents(), and so on, you're getting a pretty deep call stack. It's easy to over-use DoEvents() and accidentally fill up your call stack, resulting in a StackOverflow exception. If you're only using .DoEvents() in one or two places, you're probably okay. If it's the first tool you reach for whenever you have a long-running process, you can easily find yourself in trouble here. Even one use in the wrong place can make it possible for a user to force a stackoverflow exception (sometimes just by holding down the enter key), and that can be a security issue.
It is sometimes possible to find your same method on the call stack twice. If you didn't build the method with this in mind (hint: you probably didn't) then bad things can happen. If everything passed in to the method is a value type, and there is no dependance on things outside of the method, you might be fine. But otherwise, you need to think carefully about what happens if your entire method were to run again before control is returned to you at the point where .DoEvents() is called. What parameters or resources outside of your method might be modified that you did not expect? Does your method change any objects, where both instances on the stack might be acting on the same object?
Performance Issues. DoEvents() can give the illusion of multi-threading, but it's not real mutlithreading. This has at least three real dangers:
When you call DoEvents(), you are giving control on your existing thread back to the message pump. The message pump might in turn give control to something else, and that something else might take a while. The result is that your original operation could take much longer to finish than if it were in a thread by itself that never yields control, definitely longer than it needs.
Duplication of work. Since it's possible to find yourself running the same method twice, and we already know this method is expensive/long-running (or you wouldn't need DoEvents() in the first place), even if you accounted for all the external dependencies mentioned above so there are no adverse side effects, you may still end up duplicating a lot of work.
The other issue is the extreme version of the first: a potential to deadlock. If something else in your program depends on your process finishing, and will block until it does, and that thing is called by the message pump from DoEvents(), your app will get stuck and become unresponsive. This may sound far-fetched, but in practice it's surprisingly easy to do accidentally, and the crashes are very hard to find and debug later. This is at the root of some of the hung app situations you may have experienced on your own computer.
Usability Issues. These are side-effects that result from not properly accounting for the other dangers. There's nothing new here, as long as you looked in other places appropriately.
If you can be sure you accounted for all these things, then go ahead. But really, if DoEvents() is the first place you look to solve UI responsiveness/updating issues, you're probably not accounting for all of those issues correctly. If it's not the first place you look, there are enough other options that I would question how you made it to considering DoEvents() at all. Today, DoEvents() exists mainly for compatibility with older code that came into being before other credible options where available, and as a crutch for newer programmers who haven't yet gained enough experience for exposure to the other options.
The reality is that most of the time, at least in the .Net world, a BackgroundWorker component is nearly as easy, at least once you've done it once or twice, and it will do the job in a safe way. More recently, the async/await pattern or the use of a Task can be much more effective and safe, without needing to delve into full-blown multi-threaded code on your own.
Back in 16-bit Windows days, when every task shared a single thread, the only way to keep a program responsive within a tight loop was DoEvents. It is this non-modal usage that is discouraged in favor of threads. Here's a typical example:
' Process image
For y = 1 To height
For x = 1 to width
ProcessPixel x, y
End For
DoEvents ' <-- DON'T DO THIS -- just put the whole loop in another thread
End For
For modal things (like tracking a popup), it is likely to still be OK.
I may be wrong, but it seems to me that DoDragDrop and TrackPopupMenu are rather special cases, in that they take over the UI, so don't have the reentrancy problem (which I think is the main reason people describe DoEvents as "Evil").
Personally I don't think it's helpful to dismiss a feature as "Evil" - rather explain the pitfalls so that people can decide for themselves. In the case of DoEvents there are rare cases where it's still reasonable to use it, for example while a modal progress dialog is displayed, where the user can't interact with the rest of the UI so there is no re-entrancy issue.
Of course, if by "Evil" you mean "something you shouldn't use without fully understanding the pitfalls", then I agree that DoEvents is evil.
How would you test Ruby code that has some concurrency features? For instance, let's assume I have a synchronization mechanism that is expected to prevent deadlocks. Is there a viable way to test what it really does? Could controlled execution in fibers be the way forward?
I had the exact same problem and have implemented a simple gem for synchronizing subprocesses using breakpoints: http://github.com/remen/fork_break
I've also documented an advanced usage scenario for rails3 at http://www.hairoftheyak.com/testing-concurrency-in-rails/
I needed to make sure a gem (redis-native_hash) I authored could handle concurrent writes to the same Redis hash, detect the race condition, and elegantly recover. I found that to test this I didn't need to use threads at all.
it "should respect changes made since last read from redis" do
concurrent_edit = Redis::NativeHash.find :test => #hash.key
concurrent_edit["foo"] = "race value"
concurrent_edit.save
#hash["yin"] = "yang"
#hash["foo"] = "bad value"
#hash.save
hash = Redis::NativeHash.find :test => #hash.key
hash["foo"].should == "race value"
hash["yin"].should == "yang"
end
In this test case I just instantiated another object which represents the concurrent edit of the Redis hash, had it make a change, then make sure saving the already-existing object pointing to the same hash respected those changes.
Not all problems involving concurrency can be tested without actually USING concurrency, but in this case it was possible. You may want to try looking for something similar to test your concurrency solutions. If its possible its definitely the easier route to go.
It's definitely a difficult problem. I started writing my test using threads, and realized that they way the code I was testing was implemented, I needed the Process IDs (PID) to actually be different. Threads run using the same PID as the process that kicked off the Thread. Lesson learned.
It was at that point I started exploring forks, and came across this Stack Overflow thread, and played with fork_break. Pretty cool, and easy to set up. Though I didn't need the breakpoints for what I was doing, I just wanted processes to run through concurrently, using breakpoints could be very useful in the future. The problem I ran into was that I kept getting an EOFError and I didn't know why. So I started implementing forking myself, instead of going through fork_break, and found out it was that an exception was happening in the code under test. Sad that the stack trace was hidden from me by the EOFError, though I understand that the child process ended abruptly and that's kinda how it goes.
The next problem I came across was with the DatabaseCleaner. No matter which strategy it used (truncation, or transaction), the child process's data was truncated/rolled back when the child process finished, so the data that was inserted by child processes was gone and the parent process couldn't select and verify that it was correct.
After banging my head on that and trying many other unsuccessful things, I came across this post http://makandracards.com/makandra/556-test-concurrent-ruby-code which was almost exactly what I was already doing, with one little addition. Calling "Process.exit!" at the end of the fork. My best guess (based on my fairly limited understanding of forking) is that this causes the process to end abruptly enough that it completely bypasses any type of database cleanup when the child process ends. So my parent process, the actual test, can continue and verify the data it needs to verify. Then during the normal after hooks of the test (in this case cucumber, but could easily be rspec too), the database cleaner kicks in and cleans up data as it normally would for a test.
So, just thought I'd share some of my own lessons learned in this discusson of how to test concurrent features.
We have a bug in our application that does not occur every time and therefore we don't know its "logic". I don't even get it reproduced in 100 times today.
Disclaimer: This bug exists and I've seen it. It's not a pebkac or something similar.
What are common hints to reproduce this kind of bug?
Analyze the problem in a pair and pair-read the code. Make notes of the problems you KNOW to be true and try to assert which logical preconditions must hold true for this happen. Follow the evidence like a CSI.
Most people instinctively say "add more logging", and this may be a solution. But for a lot of problems this just makes things worse, since logging can change timing-dependencies sufficiently to make the problem more or less frequent. Changing the frequency from 1 in 1000 to 1 in 1,000,000 will not bring you closer to the true source of the problem.
So if your logical reasoning does not solve the problem, it'll probably give you a few specifics you could investigate with logging or assertions in your code.
There is no general good answer to the question, but here is what I have found:
It takes a talent for this kind of thing. Not all developers are best suited for it, even if they are superstars in other areas. So know your team, who has a talent for it, and hope you can give them enough candy to get them excited about helping you out, even if it isn't their area.
Work backwards, and treat it like a scientific investigation. Start with the bug, what you see is wrong. Develop hypotheses about what could cause it (this is the creative/imaginative part, the art that not everyone has the talent for) - and it helps a lot to know how the code works. For each of those hypotheses (preferably sorted by what you think is most likely - again pure gut feel here), develop a test that tries to eliminate it as the cause, and test the hypothesis. Any given failure to meet a prediction doesn't mean the hypothesis is wrong. Test the hypothesis until it is confirmed to be wrong (although as it gets less likely you may want to move on to another hypothesis first, just don't discount this one until you have a definitive failure).
Gather as much data as you can during this process. Extensive logging and whatever else is applicable. Do not discount a hypothesis because you lack the data, rather remedy the lack of data. Quite often the inspiration for the right hypothesis comes from examining the data. Noticing something off in a stack trace, weird issue in a log, something missing that should be there in a database, etc.
Double check every assumption. So many times I have seen an issue not get fixed quickly because some general method call was not further investigated, so the problem was just assumed to be not applicable. "Oh that, that should be simple." (See point 1).
If you run out of hypotheses, that is generally caused by insufficient knowledge of the system (this is true even if you wrote every line of code yourself), and you need to run through and review code and gain additional insight into the system to come up with a new idea.
Of course, none of the above guarantees anything, but that is the approach that I have found gets results consistently.
Add some sort of logging or tracing. For example log the last X actions the user committed before causing the bug (only if you can set a condition to match bug).
It's quite common for programmers not to be able to reiterate a user-experienced crash simply because you have developed a certain workflow and habits in using the application that obviously goes around the bug.
At this frequency of 1/100, I'd say that the first thing to do is to handle exceptions and log anything anywhere or you could be spending another week hunting this bug.
Also make a priority list of potentially sensitive articulations and features in your project. For example :
1 - Multithreading
2 - Wild pointers/ loose arrays
3 - Reliance on input devices
etc.
This will help you segment areas that you can brute-force-until-break-again as suggested by other posters.
Since this is language-agnostic, I'll mention a few axioms of debugging.
Nothing a computer ever does is random. A 'random occurrence' indicates a as-yet-undiscovered pattern. Debugging begins with isolating the pattern. Vary individual elements and assess what makes a change in the behaviour of the bug.
Different user, same computer?
Same user, different computer?
Is the occurrence strongly periodic? Does rebooting change the periodicity?
FYI- I once saw a bug that was experienced by a single person. I literally mean person, not a user account. User A would never see the problem on their system, User B would sit down at that workstation, signed on as User A and could immediately reproduce the bug. There should be no conceivable way for the app to know the difference between the physical body in the chair. However-
The users used the app in different ways. User A habitually used a hotkey to to invoke a action and User B used an on-screen control. The difference in the user behaviour would cascade into a visible error a few actions later.
ANY difference that effects the behaviour of the bug should be investigated, even if it makes no sense.
There's a good chance your application is MTWIDNTBMT (Multi Threaded When It Doesn't Need To Be Multi Threaded), or maybe just multi-threaded (to be polite). A good way to reproduce sporadic errors in multi-threaded applications is to sprinkle code like this around (C#):
Random rnd = new Random();
System.Threading.Thread.Sleep(rnd.Next(2000));
and/or this:
for (int i = 0; i < 4000000000; i++)
{
// tight loop
}
to simulate threads completing their tasks at different times than usual or tying up the processor for long stretches.
I've inherited many buggy, multi-threaded apps over the years, and code like the above examples usually makes the sporadic errors occur much more frequently.
Add verbose logging. It will take multiple -- sometimes dozen(s) -- iterations to add enough logging to understand the scenario.
Now the problem is that if the problem is a race condition, which is likely if it doesn't reproduce reliably, so logging can change timing and the problem will stop happening. In this case do not log to a file, but keep a rotating buffer of the log in memory and only dump it on disk when you detect that the problem has occurred.
Edit: a little more thoughts: if this is a gui application run tests with a qa automation tool which allows you to replay macros. If this is a service-type app, try to come up with at least a guess as to what is happening and then programmatically create 'freak' usage patterns which would exercise the code that you suspect. Create higher than usual loads etc.
What development environment?
For C++, your best bet may be VMWare Workstation record/replay, see:
http://stackframe.blogspot.com/2007/04/workstation-60-and-death-of.html
Other suggestions include inspecting the stack trace, and careful code overview... there is really no silver bullet :)
Try to add code in your app to trace the bug automatically once it happens (or even alert you via mail / SMS)
log whatever you can so when it happens you can catch the right system state.
Another thing- try applying automated testing that can cover more territory than human based testing in a formed manner.. it's a long shot, but a good practice in general.
all the above, plus throw some brute force soft-robot at it that is semi random, and scater a lot of assert/verify (c/c++, probably similar in other langs) through the code
Tons of logging and careful code review are your only options.
These can be especially painful if the app is deployed and you can't adjust the logging. At that point, your only choice is going through the code with a fine-tooth comb and trying to reason about how the program could enter into the bad state (scientific method to the rescue!)
Often these kind of bugs are related to corrupted memory and for that reason they might not appear very often. You should try to run your software with some kind of memory profiler e.g., valgrind, to see if something goes wrong.
Let’s say I’m starting with a production application.
I typically add debug logging around the areas where I think the bug is occurring. I setup the logging statements to give me insight into the state of the application. Then I have the debug log level turned on and ask the user/operator(s) notify me of the time of the next bug occurrence. I then analyze the log to see what hints it gives about the state of the application and if that leads to a better understanding of what could be going wrong.
I repeat step 1 until I have a good idea of where I can start debugging the code in the debugger
Sometimes the number of iterations of the code running is key but other times it maybe the interaction of a component with an outside system (database, specific user machine, operating system, etc.). Take some time to setup a debug environment that matches the production environment as closely as possible. VM technology is a good tool for solving this problem.
Next I proceed via the debugger. This could include creating a test harness of some sort that puts the code/components in the state I’ve observed from the logs. Knowing how to setup conditional break points can save a lot of time, so get familiar with that and other features within your debugger.
Debug, debug , debug. If you’re going nowhere after a few hours, take a break and work on something unrelated for awhile. Come back with a fresh mind and perspective.
If you have gotten nowhere by now, go back to step 1 and make another iteration.
For really difficult problems you may have to resort to installing a debugger on the system where the bug is occurring. That combined with your test harness from step 4 can usually crack the really baffling issues.
Unit Tests. Testing a bug in the app is often horrendous because there is so much noise, so many variable factors. In general the bigger the (hay)stack, the harder it is to pinpoint the issue. Creatively extending your unit test framework to embrace edge cases can save hours or even days of sifting
Having said that there is no silver bullet. I feel your pain.
Add pre and post condition check in methods related to this bug.
You may have a look at Design by contract
Along with a lot of patience, a quiet prayer & cursing you would need:
a good mechanism for logging the user actions
a good mechanism for gathering the data state when the user performs some actions (state in application, database etc.)
Check the server environment (e.g. an anti-virus software running at a particular time etc.) & record the times of the error & see if you can find any trends
some more prayers & cursing...
HTH.
Assuming you're on Windows, and your "bug" is a crash or some sort of corruption in unmanaged code (C/C++), then take a look at Application Verifier from Microsoft. The tool has a number of stops that can be enabled to verify things during runtime. If you have an idea of the scenario where your bug occurs, then try to run through the scenario (or a stress version of the scenario) with AppVerifer running. Make sure to either turn on pageheap in AppVerifier, or consider compiling your code with the /RTCcsu switch (see http://msdn.microsoft.com/en-us/library/8wtf2dfz.aspx for more information).
"Heisenbugs" require great skills to diagnose, and if you want help from people here you have to describe this in much more detail, and patiently listen to various tests and checks, report result here, and iterate this till you solve it (or decide it is too expensive in terms of resources).
You will probably have to tell us your actual situation, language, DB, operative system, workload estimate, time of the day it happened in the past, and a myriad of other things, list tests you did already, how they went, and be ready to do more and share the results.
And this will not guarantee that we collectively can find it, either...
I'd suggest to write down all things that user has been doing. If you have lets say 10 such bug reports You can try to find something that connects them.
Read the stack trace carefully and try to guess what could be happened;
then try to trace\log every line of code that potentially can cause trouble.
Keep your focus on disposing resources; many sneaky sporadical bugs i found were related to close\dispose things :).
For .NET projects You can use Elmah (Error Logging Modules and Handlers) to monitor you application for un-caught exceptions, it's very simple to install and provides a very nice interface to browse unknown errors
http://code.google.com/p/elmah/
This saved me just today in catching a very random error that was occuring during a registration process
Other than that I can only recommend trying to get as much information from your users as possible and having a thorough understanding of the project workflow
They mostly come out at night....
mostly
The team that I work with has enlisted the users in recording their time they spend in our app with CamStudio when we've got a pesky bug to track down. It's easy to install and for them to use, and makes reproducing those nagging bugs much easier, since you can watch what the users are doing. It also has no relationship to the language you're working in, since it's just recording the windows desktop.
However, this route seems to be viable only if you're developing corporate apps and have good relationships with your users.
This varies (as you say), but some of the things that are handy with this can be
immediately going into the debugger when the problem occurs and dumping all the threads (or the equivalent, such as dumping the core immediately or whatever.)
running with logging turned on but otherwise entirely in release/production mode. (This is possible in some random environments like c and rails but not many others.)
do stuff to make the edge conditions on the machine worse... force low memory / high load / more threads / serving more requests
Making sure that you're actually listening to what the users encountering the problem are actually saying. Making sure that they're actually explaining the relevant details. This seems to be the one that breaks people in the field a lot. Trying to reproduce the wrong problem is boring.
Get used to reading assembly that was produced by optimizing compilers. This seems to stop people sometimes, and it isn't applicable to all languages/platforms, but it can help
Be prepared to accept that it is your (the developer's) fault. Don't get into the trap of insisting the code is perfect.
sometimes you need to actually track the problem down on the machine it is happening on.
#p.marino - not enough rep to comment =/
tl;dr - build failures due to time of day
You mentioned time of day and that caught my eye. Had a bug once were someone stayed later at work on night, tried to build and commit before they left and kept getting a failure. They eventually gave up and went home. When they caught in the next morning it built fine, they committed (probably should have been more suspiscious =] ) and the build worked for everyone. A week or two later someone stayed late and had an unexpected build failure. Turns out there was a bug in the code that made any build after 7PM break >.>
We also found a bug in one seldom used corner of the project this january that caused problems marshalling between different schemas because we were not accounting for the different calendars being 0 AND 1 month based. So if no one had messed with that part of the project we wouldn't have possibly found the bug until jan. 2011
These were easier to fix than threading issues, but still interesting I think.
hire some testers!
This has worked for really weird heisenbugs.
(I'd also recommend getting a copy of "Debugging" by Dave Argans, these ideas are partly derived form using his ideas!)
(0) Check the ram of the system using something like Memtest86!
The whole system exhibits the problem, so make a test jig that exercises the whole thing.
Say it's a server side thing with a GUI, you run the whole thing with a GUI test framework doing the necessary input to provoke the problem.
It doesn't fail 100% of the time, so you have to make it fail more often.
Start by cutting the system in half ( binary chop)
worse case, you have to remove sub-systems one at a time.
stub them out if they can't be commented out.
See if it still fails. Does it fail more often ?
Keep proper test records, and only change one variable at a time!
Worst case you use the jig and you test for weeks to get meaningful statistics. This is HARD; but remember, the jig is doing the work.
I've got No threads and only one process, and I don't talk to hardware
If the system has no threads, no communicating processes and contacts no hardware; it's tricky; heisenbugs are generally synchronization, but in the no-thread no processes case it's more likely to be uninitialized data, or data used after being released, either on the heap or the stack. Try to use a checker like valgrind.
For threaded/multi-process problems:
Try running it on a different number of CPU's. If it's running on 1, try on 4! Try forcing a 4-computer system onto 1.
It'll mostly ensure things happen one at a time.
If there are threads or communicating processes this can shake out bugs.
If this is not helping but you suspect it's synchronization or threading, try changing the OS time-slice size.
Make it as fine as your OS vendor allows!
Sometimes this has made race conditions happen almost every time!
Obversely, try going slower on the timeslices.
Then you set the test jig running with debugger(s) attached all over the place and wait for the test jig to stop on a fault.
If all else fails, put the hardware in the freezer and run it there. The timing of everything will be shifted.
Debugging is hard and time consuming especially if you are unable to deterministically reproduce the problem. My advice to you is to find out the steps to reproduce it deterministically (not just sometimes).
There has been a lot of research in the field of failure reproduction in the past years and is still very active. Record&Replay techniques have been (so far) the research direction of most researchers. This is what you need to do:
1) Analyze the source code and determine what are the sources of non-determinism in the application, that is, what are the aspects that may take your application through different execution paths (e.g. user input, OS signals)
2) Log them in the next time you execute the application
3) When your application fails again, you have the steps-to-reproduce the failure in your log.
If your log still does not reproduce the failure, then you are dealing with a concurrency bug. In that case, you should take a look at how your application accesses shared variables. Do not attempt to record the accesses to shared variables, because you would be logging too much data, thereby causing severe slowdowns and large logs. Unfortunately, there is not much I can say that would help you to reproduce concurrency bugs, because research still has a long way to go in this subject. The best I can do is to provide a reference to the most recent advance (so far) in the topic of deterministic replay of concurrency bugs:
http://www.gsd.inesc-id.pt/~nmachado/software/Symbiosis_Tutorial.html
Best regards
Use an enhanced crash reporter. In the Delphi environment, we have EurekaLog and MadExcept. Other tools exist in other environments. Or you can diagnose the core dump. You're looking for the stack trace, which will show you where it's blowing up, how it got there, what's in memory, etc.. It's also useful to have a screenshot of the app, if it's a user-interaction thing. And info about the machine that it crashed on (OS version and patch, what else is running at the time, etc..) Both of the tools that I mentioned can do this.
If it's something that happens with a few users but you can't reproduce it, and they can, go sit with them and watch. If it's not apparent, switch seats - you "drive", and they tell you what to do. You'll uncover the subtle usability issues that way. double-clicks on a single-click button, for example, initiating re-entrancy in the OnClick event. That sort of thing. If the users are remote, use WebEx, Wink, etc., to record them crashing it, so you can analyze the playback.
I need to do some network bound calls (e.g., fetch a website) and I don't want it to block the UI. Should I be using NSThread's or python's threading module if I am working in pyobjc? I can't find any information on how to choose one over the other. Note, I don't really care about Python's GIL since my tasks are not CPU bound at all.
It will make no difference, you will gain the same behavior with slightly different interfaces. Use whichever fits best into your system.
Learn to love the run loop. Use Cocoa's URL-loading system (or, if you need plain sockets, NSFileHandle) and let it call you when the response (or failure) comes back. Then you don't have to deal with threads at all (the URL-loading system will use a thread for you).
Pretty much the only time to create your own threads in Cocoa is when you have a large task (>0.1 sec) that you can't break up.
(Someone might say NSOperation, but NSOperationQueue is broken and RAOperationQueue doesn't support concurrent operations. Fine if you already have a bunch of NSOperationQueue code or really want to prepare for working NSOperationQueue, but if you need concurrency now, run loop or threads.)
I'm more fond of the native python threading solution since I could join and reference threads around. AFAIK, NSThreads don't support thread joining and cancelling, and you could get a variety of things done with python threads.
Also, it's a bummer that NSThreads can't have multiple arguments, and though there are workarounds for this (like using NSDictionarys and NSArrays), it's still not as elegant and as simple as invoking a thread with arguments laid out in order / corresponding parameters.
But yeah, if the situation demands you to use NSThreads, there shouldn't be any problem at all. Otherwise, it's cool to stick with native python threads.
I have a different suggestion, mainly because python threading is just plain awful because of the GIL (Global Interpreter Lock), especially when you have more than one cpu core. There is a video presentation that goes into this in excruciating detail, but I cannot find the video right now - it was done by a Google employee.
Anyway, you may want to think about using the subprocess module instead of threading (have a helper program that you can execute, or use another binary on the system. Or use NSThread, it should give you more performance than what you can get with CPython threads.